The Personalization–Privacy Paradox in AI-Driven Programmatic Advertising: Implications for Digital Marketing Sustainability

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Authors: Nermin Yildirim, Bora Gündüzyeli
Cited by: 1
References: 50

Abstract

Artificial intelligence (AI) has transformed programmatic advertising (PA) by enabling automated, data-driven personalization within digital marketing ecosystems. However, this transformation has also intensified concerns regarding privacy, consumer trust, and the long-term sustainability of these ecosystems. In this study, sustainability is conceptualized as the capacity of digital marketing systems to maintain long-term functionality without eroding consumer trust or amplifying privacy-related tensions that may undermine system stability over time. This study addresses the research question: How does AI-driven PA affect the sustainability of digital marketing ecosystems through the personalization–privacy paradox? A systematic literature review, conducted in line with PRISMA guidelines, synthesizes prior research across four interrelated clusters: AI-driven personalization, privacy concerns, consumer trust, and consumer attitudes and behavior. The findings indicate that consumer responses to AI-driven personalization are not linear and are shaped by factors such as transparency, perceived control, and the perceived legitimacy of data practices. The review further shows that the paradox of personalization and privacy operates as a persistent condition within AI-driven advertising ecosystems, where the benefits of personalization coexist with ongoing privacy-related tensions. This study contributes to the literature by synthesizing fragmented research on AI-driven PA and by highlighting the central role of trust and transparency in understanding how personalization and privacy tensions shape consumer responses in digital marketing ecosystems.

Fields of Study & Subjects

AI in Service Interactions Digital Marketing and Social Media Privacy Security and Data Protection

Publication details

Journal / source
Journal of theoretical and applied electronic commerce research
Publisher
MDPI AG
Volume
21
Issue
6
Pages
179–179
Publication date
5 June 2026
Language
EN